As I didn't really know exactly how to answer, I started to do some tests myself to understand it better.
I've used the same very simple file, just to not complicate things too much...
Always generating a line from 4 points, I moved the two central points using Galapagos, to obtain the curve closer to an attraction point. (you can get the GH file here).
The 4 points start as indicated (A, B), and in the image below you can see what happens after 10 tests (50 generations each):
As I was expecting, all the results are different... (but valid, as they are very close to the attractor point)... cool!
But if you do the test starting from this configuration (see below...) you will obtain all the solutions identical! This is an image with 10 solutions all identical, after running 50 generations 10 times:
I was quite surprised.
So why before I was obtaining random results, and now not?
The "randomness" seems to be related to the starting value of the sliders (starting position of the points).
- If you start with the points very close to an acceptable solution, the final results are very similar between each other... (in the previous case, the starting points were coincident to a solution, so after generations, there was no change, so all the solutions are identical)
- If you start with the points very far from an acceptable solution, the final results are very different from each other.
How random the results are of course depends also on the "freedom" of the genes... So if I increase the sliders range, I would obtain more random results...
If you re-do the test, starting with points distant from the solution, this is the result after 10 tests (again 50 generations each):
I'm looking forward for a manual about Galapagos, to have a better understanding of the generative process!
For the moment a great tool to learn more is the lecture that David Rutten did at AA in London:
Lecture of David Rutten - evolutionary principles.